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采矿单细胞时间序列数据集使用时间轨迹检查器.

Maciej Dobrzyński1, Marc-Antoine Jacques1, Olivier Pertz1

  • 1Institute of Cell Biology, University of Bern, Bern 3012, Switzerland.

Bioinformatics (Oxford, England)
|December 14, 2023
PubMed
概括

活细胞成像技术的近期进步产生了大量单细胞时间序列数据. 时间过程检查器 (TCI) 是一款新的R/Shiny工具,它将时间序列分析与聚类相结合,以识别具有独特时间行为的细胞子群.

科学领域:

  • 细胞生物学 细胞生物学
  • 计算生物学是一种计算生物学.
  • 生物信息学是一种生物信息学.

背景情况:

  • 活细胞成像和生物传感器技术使高通量单细胞时间序列数据生成成为可能.
  • 识别不同的细胞亚种群及其动态行为对于理解细胞命运决定至关重要.

研究的目的:

  • 开发一种用于分析大型单细胞时间序列数据集的新型计算工具.
  • 为了方便识别具有独特时间动态的子群体.

主要方法:

  • 时间轨迹检查器 (TCI) 的开发,这是一个在R/Shiny中实现的工具.
  • 时间序列分析与等级集群和集群验证方法的整合.
  • 交互式数据探索,可视化和异常值删除功能.

主要成果:

  • TCI可以方便地检查和分析单细胞时间序列数据.
  • 该工具促进了对各种集群方法的交互探索.
  • 在分析基于光生物传感器的单细胞信号数据集中,TCI的实用性得到证明.

结论:

  • 时间课程检查器 (TCI) 是分析复杂单细胞时间序列数据的有效工具.

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  • TCI有助于识别具有独特时间行为的细胞子群体,这对于细胞命运的决定至关重要.
  • 该工具增强了对显微镜衍生生物传感器数据的分析.